Inside GNSS Media & Research

NOV-DEC 2018

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32 InsideGNSS N O V E M B E R / D E C E M B E R 2 0 1 8 times, equation 4 can be used to calcu- late the pseudorange for each satellite. It should be noted that, although the error ( ) in the coarse initial received time ( ) can be used in pseu- dorange construction without inducing pseudorange error, it will still induce an error in the satellite ephemeris calculation. In conventional GNSS processing, fine time is known well enough to be sufficient to be directly applied for position estimation. For any coarse time positioning method, the absolute time error must be an addi- tional estimation state. e Position Estimation in snap- shot positioning can be implemented as an independent least-squares calcu- lation or in a Kalman filter. e solu- tion update interval is customizable for different use cases. In cases where position is only needed at infrequent intervals, accuracy requirements are usually less stringent and a least squares solution is sufficient even with the extra estimated absolute time error. With more frequent updates, a Kalman filter can be used to improve solution accuracy. Conceptual Structure of a Snapshot Receiver In a snapshot receiver, each Signal Capture is digitized and saved as a data file. e user has full control over how oen and how many milliseconds of digital samples to capture. Signal pro- cessing is a key differentiator between the state of the art snapshot receiver and the conventional receiver. When compared with conven- tional GNSS receivers, there is a lot of flexibility when designing a snapshot receiver. A conventional receiver usu- ally performs all the blocks of Signal Capture, Signal Processing, and Position Estimation in the hardware device, even if measurements are output for later post-processing. In contrast, a snapshot receiver can be designed to distribute these blocks to optimize energy consumption for their unique hardware platform and, indeed, use cases as described below. As mentioned earlier, Signal Pro- FIGURE 2 Example structure of a snapshot receiver that only performs signal capture on device, and defers signal processing and position estimation to a cloud server to reduce power consumption on the device FIGURE 3 Example structure of a snapshot receiver where all processing is performed on the device with ephemeris information being provided by a cloud server FIGURE 4 Example structure of a snapshot receiver where signal processing is per- formed on device, but position estimation is performed on an external server cessing and Position Estimation can be performed long aer the signal data has been captured. For use cases where maximizing battery life is more critical than real-time positioning, the snapshot receiver can be configured such that only the Signal Capture cir- cuitry is implemented to temporarily store the digital samples. Signal pro- cessing will be postponed until such a time that the digital samples can be transmitted, without affecting the battery life of the device (e.g. during battery recharge), to a remote cloud server for Signal Processing and Posi- tion Estimation computations. is is illustrated in Figure 2. For use cases where a position information is needed at the device, the snapshot receiver can be configured such that the Signal Capture, Signal Processing, Position Estimation blocks are all implemented on a single cir- cuitry, where the extended ephemeris is retrieved from a cloud server at time intervals that has the least impact on the battery life. Such a setup is illus- trated in Figure 3. Figure 4 shows a hybrid of the above two use cases, where the snapshot receiver is be configured to capture the digital sample data and then generates measurements prior to transmitting the pre-processed measurements to the remote cloud server for the final Position Estimation computation. In this approach, power consumed for transmitting measurement data is much smaller than for digital samples. Furthermore, the server can estimate a better position solution since it has access to precise orbits. GNSS SOLUTIONS

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